Cloud MSPs or managed service providers are great at helping companies properly leverage the public cloud, typically handling cloud strategy, implementation and day-to-day operations for their customers. However, when it comes to things like customizable billing, analyzing cloud spend per customer, optimizing cost and increasing profit margins, MSPs are over-burdened with complex, manual processes.

When buying AWS Savings Plans and RIs, Spot Eco makes it easy to create a highly utilized and well-balanced blend of Savings Plans and RIs. Leveraging 3rd party Standard RIs (with shorter terms) alongside Convertible RIs, and Savings Plans, Eco helps ensure maximum savings with minimum commitment.

AWS is one of the primary providers for services that help users deploy and manage their containerized applications on the cloud. Since launching ECS in 2014 and EKS in 2017, AWS has learned a lot about running containers at scale and in production. AWS developed Bottlerocket OS, a new operating system for hosting containers. This OS was specifically designed to address gaps left by the ECS and EKS-optimized AMIs, which are based on operating systems that run traditional software applications.

We often encounter companies who are end-customers of a Cloud MSP (Managed Service Provider) and/or reseller of AWS products and services. In these cases, the end-customer may not have access to the AWS Management Account because the MSP owns it and restricts access for security reasons.

As we develop and deploy cloud compute automation and optimization solutions here at Spot by NetApp, we use various tools to improve our day-to-day operations. In this post I’ll share how we’ve found Terraform Cloud from Hashicorp to be quite helpful with deployment management.

Security remains a consistent priority for cloud providers to ensure that customers are always protected, data is secure and applications are safe. Users of Google Kubernetes Engine (GKE) are provided with ways to maintain the integrity of the compute instances that applications are running on top of.

When running AKS clusters, ideally you want the compute infrastructure to adapt to your Kubernetes workload and not the other way around. VMs should automatically match your application requirements all the time without labor-intensive, hands-on management, and of course, your Azure bill should be as low-cost as possible. However, in trying to achieve this ideal, AKS and Kubernetes users in general, still face significant operational challenges.

It’s been six years since Kubernetes v1.0 was released in 2015, and since then it’s become a critical technology foundation to deploy modern, cloud native applications with speed, develop them with agility and scale them with flexibility. With a fast-maturing ecosystem, advancements in tooling are making it possible for a new wave of applications to be deployed on Kubernetes.